Fuzzy logic power system stabilizer in multimachine stability studies

Power system stabilizers (PSS) work well at the particular network configuration and steady state conditions for which they were designed. Once conditions change, their performance degrades. This can be overcome by an intelligent nonlinear PSS based on fuzzy logic. Such a fuzzy logic power system stabilizer (FLPSS) is developed, using speed and power deviation as inputs, and provides an auxiliary signal for the excitation system of a synchronous motor in a multimachine power system environment. The FLPSS's effect on the system damping is then compared with a conventional power system stabilizer's (CPSS) effect on the system. The results demonstrate an improved system performance with the FLPSS and also that the FLPSS is robust

Stability boundary analysis of the dynamic voltage restorer in weak systems with dynamic loads

In this contribution, a stability analysis for a dynamic voltage restorer (DVR) connected to a weak ac system containing a dynamic load is presented using continuation techniques and bifurcation theory. The system dynamics are explored through the continuation of periodic solutions of the associated dynamic equations. The switching process in the DVR converter is taken into account to trace the stability regions through a suitable mathematical representation of the DVR converter. The stability regions in the Thevenin equivalent plane are computed. In addition, the stability regions in the control gains space, as well as the contour lines for different Floquet multipliers, are computed. Besides, the DVR converter model employed in this contribution avoids the necessity of developing very complicated iterative map approaches as in the conventional bifurcation analysis of converters. The continuation method and the DVR model can take into account dynamics and nonlinear loads and any network topology since the analysis is carried out directly from the state space equations. The bifurcation approach is shown to be both computationally efficient and robust, since it eliminates the need for numerically critical and long-lasting transient simulations.

Small-signal stability analysis of a DFIG-based wind power system under different modes of operation

This paper focuses on the super/subsynchronous operation of the doubly fed induction generator (DFIG) system. The impact of a damping controller on the different modes of operation for the DFIG-based wind generation system is investigated. The coordinated tuning of the damping controller to enhance the damping of the oscillatory modes using bacteria foraging technique is presented. The results from eigenvalue analysis are presented to elucidate the effectiveness of the tuned damping controller in the DFIG system. The robustness issue of the damping controller is also investigated.

Robust speed tracking control of synchronous motors using immersion and invariance

This paper presents a novel control strategy for velocity tracking of Permanent Magnet Synchronous Machines (PMSM). The model of the machine is considered within the port-Hamiltonian framework and a control is designed using concepts of immersion and invariance (I&I) recently developed in the literature. The proposed controller ensures internal stability and output regulation, and it forces integral action on non-passive outputs.

CCD: Connected Component Descriptor for Robust Mosaicing of Camera-Captured Document Images

We propose a robust method for mosaicing of document images using features derived from connected components. Each connected component is described using the Angular Radial Tran. form (ART). To ensure geometric consistency during feature matching, the ART coefficients of a connected component are augmented with those of its two nearest neighbors. The proposed method addresses two critical issues often encountered in correspondence matching: (i) The stability of features and (ii) Robustness against false matches due to the multiple instances of characters in a document image. The use of connected components guarantees a stable localization across images. The augmented features ensure a successful correspondence matching even in the presence of multiple similar regions within the page. We illustrate the effectiveness of the proposed method on camera captured document images exhibiting large variations in viewpoint, illumination and scale.

A new intelligent algorithm for online voltage stability assessment and monitoring

This paper presents a new approach for assessing power system voltage stability based on artificial feed forward neural network (FFNN). The approach uses real and reactive power, as well as voltage vectors for generators and load buses to train the neural net (NN). The input properties of the NN are generated from offline training data with various simulated loading conditions using a conventional voltage stability algorithm based on the L-index. The performance of the trained NN is investigated on two systems under various voltage stability assessment conditions. Main advantage is that the proposed approach is fast, robust, accurate and can be used online for predicting the L-indices of all the power system buses simultaneously. The method can also be effectively used to determining local and global stability margin for further improvement measures.

Tetragonal bismuth bilayer: A stable and robust quantum spin hall insulator

Topological insulators (TIs) exhibit novel physics with great promise for new devices, but considerable challenges remain to identify TIs with high structural stability and large nontrivial band gap suitable for practical applications. Here we predict by first-principles calculations a two-dimensional (2D) TI, also known as a quantum spin Hall (QSH) insulator, in a tetragonal bismuth bilayer (TB-Bi) structure that is dynamically and thermally stable based on phonon calculations and finite-temperature molecular dynamics simulations. Density functional theory and tight-binding calculations reveal a band inversion among the Bi-p orbits driven by the strong intrinsic spin-orbit coupling, producing a large nontrivial band gap, which can be effectively tuned by moderate strains. The helical gapless edge states exhibit a linear dispersion with a high Fermi velocity comparable to that of graphene, and the QSHphase remains robust on a NaCl substrate. These remarkable properties place TB-Bi among the most promising 2D TIs for high-speed spintronic devices, and the present results provide insights into the intriguing QSH phenomenon in this new Bi structure and offer guidance for its implementation in potential applications.

Stability of synchronization in a multi-cellular system

Networks of biochemical reactions regulated by positive-and negative-feedback processes underlie functional dynamics in single cells. Synchronization of dynamics in the constituent cells is a hallmark of collective behavior in multi-cellular biological systems. Stability of the synchronized state is required for robust functioning of the multi-cell system in the face of noise and perturbation. Yet, the ability to respond to signals and change functional dynamics are also important features during development, disease, and evolution in living systems. In this paper, using a coupled multi-cell system model, we investigate the role of system size, coupling strength and its topology on the synchronization of the collective dynamics and its stability. Even though different coupling topologies lead to synchronization of collective dynamics, diffusive coupling through the end product of the pathway does not confer stability to the synchronized state. The results are discussed with a view to their prevalence in biological systems. Copyright (C) EPLA, 2010

A Neuro-Adaptive Approach for Robust Control of High Performance Aircrafts with Parameter Inaccuracies

For high performance aircrafts, the flight control system needs to be quite effective in both assuring accurate tracking of pilot commands, while simultaneously assuring overall stability of the aircraft. In addition, the control system must also be sufficiently robust to cater to possible parameter variations. The primary aim of this paper is to enhance the robustness of the controller for a HPA using neuro-adaptive control design. Here the architecture employs a network of Gaussian Radial basis functions to adaptively compensate for the ignored system dynamics. A stable weight mechanism is determined using Lyapunov theory. The network construction and performance of the resulting controller are illustrated through simulations with a low-fidelity six –DOF model of F16 that is available in open literature.

Experimental and Numerical Studies in a Compact Trapped Vortex Combustor: Stability Assessment and Augmentation

Fundamental studies on a compact trapped vortex combustor indicate that cavity injection strategies play a major role on flame stability. Detailed experiments indicate that blow-out occurs for a certain range of cavity air flow velocities. An unsteady RANS-based reacting flow simulation tool has been utilized to study the basic dynamics of cavity vortex for various flow conditions. The phenomenon of flame blow-out at certain intermediate cavity air velocities is explained on the basis of transition from a cavity-stabilized mode to an opposed flow stagnation mode. A novel strategy is proposed for achieving flame stability at all conditions. This involves using a flow guide vane in the path of the main flow to direct a portion of the main flow into the cavity. This seems to result in a desirable dual vortex structure, i.e., a small clockwise vortex behind the vane and large counterclockwise vortex in the cavity. Experimental results show stable flame at all flow conditions with the flow guide vane, and pressure drop is estimated to be within acceptable limits. Cold flow simulations show self-similar velocity profiles for a range of main inlet velocities, and high reverse velocity ratios (-0.3) are observed. Such a high-velocity ratio in the reverse flow shear layer profile leads to enhanced production of turbulence imperative to compact combustors. Reacting flow simulations show even higher reverse velocity ratios (above -0.7) due to flow acceleration. The flame is observed to be stable, even though minor shear layer oscillations are present in the form of vortex shedding. Self-similarity is also observed in reacting flow temperature profiles at combustor exit over the entire range of the mainstream velocity. This indicates that the present configuration holds a promise of delivering robust performance invariant of the flow operating conditions.

Novel algorithm for online voltage stability assessment based on feed forward neural network

This paper presents an artificial feed forward neural network (FFNN) approach for the assessment of power system voltage stability. A novel approach based on the input-output relation between real and reactive power, as well as voltage vectors for generators and load buses is used to train the neural net (NN). The input properties of the feed forward network are generated from offline training data with various simulated loading conditions using a conventional voltage stability algorithm based on the L-index. The neural network is trained for the L-index output as the target vector for each of the system loads. Two separate trained NN, corresponding to normal loading and contingency, are investigated on the 367 node practical power system network. The performance of the trained artificial neural network (ANN) is also investigated on the system under various voltage stability assessment conditions. As compared to the computationally intensive benchmark conventional software, near accurate results in the value of L-index and thus the voltage profile were obtained. Proposed algorithm is fast, robust and accurate and can be used online for predicting the L-indices of all the power system buses. The proposed ANN approach is also shown to be effective and computationally feasible in voltage stability assessment as well as potential enhancements within an overall energy management system in order to determining local and global stability indices

Robust dielectric properties of B-site size-disordered hexagonal Ln(2)CuTiO(6) (Ln = Y, Dy, Ho, Er, and Yb)

Hexagonal Ln(2)CuTiO(6) (Ln = Y, Dy, Ho, Er, and Yb) exhibits a rare combination of interesting dielectric properties, in the form of relatively large dielectric constants (epsilon' > 30), low losses, and extremely small temperature and frequency dependencies, over large ranges of temperature and frequency Choudhury et al., Appl. Phys. Lett. 96, 162903 (2010) and Choudhury et al., Phys. Rev. B 82, 134203 (2010)], making these compounds promising as high-k dielectric materials. The authors present a brief review of the existing literature on this interesting class of oxides, complimenting it with spectroscopic data in conjunction with first-principles calculation results, revealing a novel mechanism underlying these robust dielectric properties. These show that the large size differences in Cu2+ and Ti4+ at the B-site, aided by an inherent random distribution of CuO5 and TiO5 polyhedral units, frustrates the ferroelectric instability, inherent to the noncentrosymmetric P6(3) cm space group of this system, and gives rise to the observed relatively large dielectric constant values. Additionally, the phononic contributions to the dielectric constant are dominated primarily by mid-frequency (>100 cm(-1)) polar modes, involving mainly Ti4+ 3d(0) ions. In contrast, the soft polar phonon modes with frequencies typically less than 100 cm(-1), usually responsible for dielectric properties of materials, are found to be associated with non-d(0) Cu2+ ions and to contribute very little, giving rise to the remarkable temperature stability of dielectric properties of these compounds. (C) 2014 American Vacuum Society.

Stress reduction and bond stability during thermal annealing of tetrahedral amorphous carbon

A comprehensive study of the stress release and structural changes caused by postdeposition thermal annealing of tetrahedral amorphous carbon (ta-C) on Si has been carried out. Complete stress relief occurs at 600-700°C and is accompanied by minimal structural modifications, as indicated by electron energy loss spectroscopy, Raman spectroscopy, and optical gap measurements. Further annealing in vacuum converts sp3 sites to sp2 with a drastic change occurring after 1100°C. The field emitting behavior is substantially retained up to the complete stress relief, confirming that ta-C is a robust emitting material. © 1999 American Institute of Physics.

Optimally robust shortcuts to population inversion in two-level quantum systems

19 p.

Robust speed control for a variable speed wind turbine

Modern wind turbines are designed in order to work in variable speed opera-tions. To perform this task, these turbines are provided with adjustable speed generators, like the double feed induction generator (DFIG). One of the main advantages of adjustable speed generators is improving the system efficiency compared with _xed speed generators, because turbine speed can be adjusted as a function of wind speed in order to maximize the output power. However, this system requires a suitable speed controller in order to track the optimal reference speed of the wind turbine. In this work, a sliding mode control for variable speed wind turbines is proposed. The proposed design also uses the vector oriented control theory in order to simplify the DFIG dynamical equations. The stability analysis of the proposed controller has been carried out under wind variations and pa-rameter uncertainties using the Lyapunov stability theory. Finally, the simulated results show on the one hand that the proposed controller provides a high-performance dynamic behavior, and on the other hand that this scheme is robust with respect to parameter uncertainties and wind speed variations, which usually appear in real systems.